Abstract

Relocalisation in 6D is relevant to a variety of
Robotics applications and in particular to agile cameras ex-
ploring a 3D environment. While the geometry and appearance
has been used by several relocalisation systems before, we
are interested in using 3D information to assist faster robust
pose estimation. Our approach rapidly searches for a reduced
number of visual descriptors previously observed and stored in
a database, that can be used to effectively compute the camera
pose corresponding to the current view. We propose to guide
the search by means of constructing validated sets using a 3D
test involving the depth information obtained with an RGB-
D or stereo camera. Our experiments demonstrate that this
guided search returns a compact quality set that works better
for the camera pose estimation stage than when using a typical
1-Nearest-Neighbour search over the candidate descriptors. The
improvements are observed in terms of percentage of relocalised
frames and speed, where the latter goes up to two order of
magnitude w.r.t. the conventional search.